Impact Behavior of Sustainable Sandwich Panels with Flax FRP Faces and Cardboard Cores
Bibliographic record
Abstract
Structural sandwich panels have been shown to be effective for use as building cladding materials due to their low weight and high relative strength and stiffness. To increase the sustainability of these panels natural and recyclable materials can be used in place of the traditional synthetic materials such as metals, synthetic fiber-reinforced polymers (FRPs), and foams. In this study, a total of six large-scale sandwich panels with flax fiber-reinforced polymer (FFRP) faces and cardboard cores were fabricated and tested under quasi-static and impact loads. The FFRP faces were made using two layers of a bidirectional woven flax fabric and a bio-based epoxy with a reported bio-content of 30%. The cores were made of sections of corrugated cardboard. The panels were tested under both quasi-static three-point bending and using a drop weight impact. The drop weight impact was designed such that the energy matched the failure energy observed during the static tests. The specimens were 150 mm wide, 75 mm thick, and 1,200 mm long and were impacted by a 150 mm impact surface at midspan. A string potentiometer was used to measure deflection at the midspan and strain gauges were applied to the top and bottom faces at midspan. The data was acquired at a rate of 10 Hz for the static tests and 25 kHz for the impact test. The aim of this project is to provide data to the growing field of study, present a deeper understanding of impact on FFRP sandwich panels, and to show the viability of natural and recycled materials for use in sustainable sandwich panels as cladding in new infrastructure. Another aim of this research is to show that materials which are often not considered due to limiting factors, such as moisture resistance, can be used with minor modifications and should not be discounted. This is on-going research and results will be available for the submission of the full paper.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".